AI decisions: Why Transparency Is Indispensable

Artificial Intelligence (AI) is increasingly being used in areas that have a direct impact on our lives. The range of possible applications includes everything from medical diagnostics to loan approvals and government processes. But before we entrust AI systems with the responsibility for far-reaching decisions, transparency must be ensured. Only then can risks and inequalities be avoided.

The Challenge of AI-Supported Decisions

AI systems can analyze large amounts of data and derive decisions or recommendations from them. This raises the question of who is responsible when a system makes incorrect or unfair decisions. Especially in cases that directly affect people, AI must never be the final authority.

Unlike humans, AI cannot fully grasp all individual life realities, cultural particularities, and social differences. It operates based on patterns present in its training data – and that data is never complete or entirely free from bias.

Inequalities in Training Data

A central problem lies in the composition of the data. Many AI systems are trained on datasets that primarily reflect the life realities of wealthier regions. The so-called Global South – particularly many African countries – is often underrepresented in this data.

These gaps can lead to AI-based decisions unintentionally disadvantaging certain population groups. A similar problem arises for people who are financially disadvantaged or living on the margins of society. Their living conditions are barely or insufficiently represented in the datasets, meaning the AI can account for their needs and risks only poorly.

Why Transparency Is Crucial

As long as it is unclear which data an AI is based on and how that data influences its decisions, it is dangerous to entrust it with far-reaching responsibility. In this context, transparency means disclosing:

• Which data sources are used,
• Which population groups are represented – and which are not,
• Which potential biases result from this data.

Only when these factors are transparent and understandable can risks be purposefully mitigated.

Conclusion: Human Responsibility Remains Essential

Before AI systems are allowed to make independent decisions in sensitive areas, transparency and comprehensibility must be guaranteed. Until then, humans should remain the final decision-makers – especially where direct impacts on people and their living conditions are concerned.